Abstract

Using the LePage representation, a symmetric alpha-stable random element in Banach space B with alpha from (0,2) can be represented as a sum of points of a Poisson process in B. This point process is union-stable, i.e. the union of its two independent copies coincides in distribution with the rescaled original point process. This shows that the classical definition of stable random elements is closely related to the union-stability property of point processes. These concepts make sense in any convex cone, i.e. in a semigroup equipped with multiplication by numbers, and lead to a construction of stable laws in general cones by means of the LePage series. We prove that random samples (or binomial point processes) in rather general cones converge in distribution in the vague topology to the union-stable Poisson point process. This convergence holds also in a stronger topology, which implies that the sums of points converge in distribution to the sum of points of the union-stable point process. Since the latter corresponds to a stable law, this yields a limit theorem for normalised sums of random elements with alpha-stable limit for alpha from (0,1). By using the technique of harmonic analysis on semigroups we characterise distributions of alpha-stable random elements and show how possible values of the characteristic exponent alpha relate to the properties of the semigroup and the corresponding scaling operation, in particular, their distributivity properties. It is shown that several conditions imply that a stable random element admits the LePage representation. The approach developed in the paper not only makes it possible to handle stable distributions in rather general cones (like spaces of sets or measures), but also provides an alternative way to prove classical limit theorems and deduce the LePage representation for strictly stable random vectors in Banach spaces.

Highlights

  • Stability of random elements is one of the basic concepts in probability theory

  • We show that in case α ∈ (0, 1) this convergence holds in a stronger topology that ensures the convergence of sums of points from point processes

  • Further we describe several essential properties of cones and semigroups that have a particular bearing in view of the properties of stable distributions

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Summary

Introduction

Stability of random elements is one of the basic concepts in probability theory. A random vector ξ with values in a Banach space B has a strictly stable distribution with characteristic exponent α = 0 (notation SαS) if, for all a, b > 0, a1/αξ1 + b1/αξ2 =D (a + b)1/αξ ,. We address this question by comparing the integral representations of Laplace exponents with the formula for the probability generating functional of a stable Poisson process. We first show that the sum of points of a union-stable Poisson point process follows SαS law, demonstrate that convergence of point processes yields a limit theorem with SαS limiting distribution, and prove that in a rather general case any SαS random element with α ∈ (0, 1) can be represented as a sum of points of a Poisson process. Even in this case we come up with new proofs that further our understanding of stable laws in linear spaces

Basic definitions
Origin and neutral element
Norm and metric
Sub-invariance
Point processes on a cone
Stable Poisson process
LePage series
Levy process
Weak convergence of point processes
Convergence of binomial processes
Convergence of sums
Domains of attraction for SαS laws
Characters on semigroups
Laplace transform
Characterisation of Laplace transforms for SαS elements
Possible values of α for SαS distributions
Integral representations of negative definite functions
Levy measures of SαS laws
Quadratic form and Levy function
Symmetric random elements
LePage series on the second dual semigroup
Support of the Levy measure
LePage series constructed from the Levy measure
LePage series representation on semigroups
Cones with the second distributivity law
Cones without the second distributivity law
Cones violating basic assumptions
Full Text
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